ProblemsTRC

先进PID，在MATLAB环境下编程，便于初学者进行交流，不足之处还望指导。(Advanced PID, in the MATLAB programming environment, easy for beginners to communicate, less than the guidance of the Office also hope.)

说明：  Crank-Nicolson格式求解抛物型方程(Solving parabolic equation with crank Nicolson scheme)

说明：  传染病模型是指传染病的基本数学模型，研究传染病的传播速度、空间范围、传播途径、动力学机理等问题，以指导对传染病的有效的预防和控制。常见的传染病模型按照传染病类型分为SI、SIR、SIRS、SEIR模型等。由于2019年末出现的新冠肺炎有一定的潜伏期，与病人接触过的健康人并不马上患病，而是称为病原体的携带者，归为E类。(infectious disease model simulation)

Matlab Codes for MST-MinimumSpaning tree

voc 分类 Object Detection with Discriminatively Trained Part Based Models(voc Category Object Detection with Discriminatively Trained Part Based Models)

利用总体变分法实现图像去噪，内有详细说明和事例(Variational method used to achieve the overall image denoising, with detailed descriptions and examples)

matlab7.0应用编程，中文资料，每章一个文件(Application Programming matlab7.0, English information, each devoted to a file)

实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))

小波与近似熵相结合的机械振动噪声信号分析 8.复morlet小波实验程序.(8 Complex Wavelet morlet experimental procedures.)

正交信号校正，用于处理红外及近红外光谱数据，以改进定量校正模型精度(OSC for processing infrared and near-infrared spectral data in order to improve the accuracy of quantitative calibration model)